Biology subjects

Liang, Y.

Publications and source records attributed to Liang, Y..

17 recordsLinked to original sources

bioRxiv2018

Optical Sectioning of Live Mammal with Near-Infrared Light Sheet

Deep-tissue three-dimensional optical imaging of live mammals in vivo with high spatiotemporal resolution in non-invasive manners has been challenging due to light scattering. Here, we developed near-infrared (NIR) light sheet microscopy (LSM) with optical excitation and emission wavelengths up to ~ 1320 nm and ~ 1700 nm respectively, far into the NIR-II (1000-1700 nm) region for 3D optical sectioning through live tissues. Suppressed scattering of both excitation and emission photons allowed one-photon optical sectioning at ~ 2 mm depth in highly scattering brain tissues. NIR-II LSM enabled non-invasive in vivo imaging of live mice, revealing never-before-seen dynamic processes such as highly abnormal tumor microcirculation, and 3D molecular imaging of an important immune checkpoint protein, programmed-death ligand 1 (PD-L1) receptors at the single cell scale in tumors. In vivo two-color near-infrared light sheet sectioning enabled simultaneous volumetric imaging of tumor vasculatures and PD-L1 proteins in live mammals.

bioengineering↗

bioRxiv2018

An \"inverse approach\" to the treatment of amblyopia

Recent laboratory finding suggest that short-term patching the amblyopic eye (i.e., inverse occlusion) results in a larger and more sustained improvement in the binocular balance compared with normal controls. In this study, we investigate the cumulative effects of the short-term inverse occlusion in adults and old children with amblyopia. A prospective cohort study of 18 amblyopes (10-35 years old; 3 with strabismus) who have been subjected to 2 hours/day of inverse occlusion for 2 months. Patients who required refractive correction or whose refractive correction needed updating were given a 2-month period of refractive adaptation. The primary outcome measure was the binocular balance which was measured using a phase combination task, the secondary outcome measures were the best corrected visual acuity which was measured with a Tumbling E acuity chart and convert to logMAR units and the stereo acuity which was measured with the Random-dot preschool stereotest. The averaged binocular gain was 0.11 in terms of the effective contrast ratio (z = -2.344, p = 0.019, 2-tailed Related samples Wilcoxon Signed Ranks Test). The average acuity gain was 0.14 logMAR equivalent (t(17) = 0.13, p < 0.001, 2-tailed paired samples t-test). The averaged stereo acuity gain was 253 arc seconds (z = -2.689, p = 0.007). Based on more recent research concerning adult ocular dominance plasticity, contrary to current practice, patching the amblyopic eye makes more sense; comparable acuity benefits, better compliance, better binocular outcome and applicable to adults as well as old children.

neuroscience↗

bioRxiv2018

Glutamate spillover in C. elegans triggers repetitive behavior through presynaptic activation of MGL-2/mGluR5

Glutamate is a major excitatory neurotransmitter, and impaired glutamate clearance following synaptic release promotes spillover, inducing extra-synaptic signaling. The effects of glutamate spillover on animal behavior and its neural correlates are poorly understood. We developed a glutamate spillover model in Caenorhabditis elegans by inactivating the conserved glial glutamate transporter GLT-1. GLT-1 loss drives aberrant repetitive locomotory reversal behavior through uncontrolled oscillatory release of glutamate onto AVA, a major interneuron governing reversals. Repetitive glutamate release and reversal behavior require the glutamate receptor MGL-2/mGluR5, expressed in RIM and other interneurons presynaptic to AVA. mgl-2 loss blocks oscillations and repetitive behavior; while RIM activation is sufficient to induce repetitive reversals in glt-1 mutants. Repetitive AVA firing and reversals require EGL-30/Gq, an mGluR5 effector. Our studies reveal that cyclic autocrine presynaptic activation drives repetitive reversals following glutamate spillover. That mammalian GLT1 and mGluR5 are implicated in pathological motor repetition suggests a common mechanism controlling repetitive behaviors.

neuroscience↗

bioRxiv2018

Receptor Mediated Delivery of Cas9-Nanobody Induces Cisplatin Synthetic Dose Sensitivity

The CRISPR/Cas9 system has shown great potential for precisely editing genomic DNA sequences by introducing site-specific DNA cuts that are subsequently repaired by the cell. However, delivery of the CRISPR ribonucleoprotein remains an understudied area and hinders realizing the full potential of the system. We prepared Cas9 ribonucleoprotein complexes chemically conjugated to the 7D12 nanobody and demonstrate receptor-mediated transfection of Cas9 into A549 non-small-cell lung cancer cells via binding to the epithelial growth factor receptor for subsequent cell internalization. We further show that transfection with a Cas9 ribonucleoprotein targeting the BRCA2 gene results in an enhanced sensitivity to the chemotherapeutic drug Cisplatin, and thereby induces a synthetic dose lethality in A549 cells.

biochemistry↗

bioRxiv2018

GONST2 transports GDP-Mannose for sphingolipid glycosylation in the Golgi apparatus of Arabidopsis

The Golgi lumen is the site of many different glycosylation events, including cell wall polysaccharide biosynthesis and lipid glycosylation. Transporters are necessary for the import of the substrates required for glycosylation (nucleotide sugars) from the cytosol where they are synthesized. Plants use four GDP-linked sugars to glycosylate macromolecules: GDP-L-Fucose, GDP-D-Mannose, GDP-L-Galactose and GDP-D-Glucose. Of the predicted fifty-one members of the nucleotide sugar transporter/triose phosphate transporter family in Arabidopsis, only four appear to contain the conserved motif needed for the transport of GDP-linked sugars, GOLGI LOCALIZED NUCLEOTIDE SUGAR TRANSPORTER (GONST) 1-4. Previously, we have demonstrated that GONST1 provides GDP-D-Mannose for glycosylation of a class of sphingolipids, the glycosylinositolphosphorylceramides (GIPCs). Here, we characterize its closest homologue, GONST2, and conclude that it also specifically provides substrate for GIPC glycosylation. Expression of GONST2 driven by the GONST1 promoter is able to rescue the severe growth phenotype of gonst1. Loss of GONST2 exacerbates the gonst1 constitutive hypersensitive response, as well as the reduced cell wall cellulose content. The gonst2 mutant grows normally under standard conditions, but has enhanced resistance to the powdery mildew-causing fungus Golovinomyces orontii.

plant biology↗

bioRxiv2018

Antimicrobial Activity of Tetrabromobisphenol A (TBBPA) against Staphylococcus aureus Skin Infections

Tetrabromobisphenol A (TBBPA) is a brominated flame retardant with selective antimicrobial activity against Gram-positive bacteria. We show that TBBPA exerts bactericidal effects by damaging the cell wall and membrane of Staphylococcus aureus (SA) without inducing antimicrobial resistance. In vivo skin infection assays indicate that a low dose of TBBPA could contribute to wound closure and attenuate SA infection and inflammatory infiltration. TBBPA has potential for use as an antimicrobial agent against Gram-positive pathogens.

microbiology↗

bioRxiv2018

Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data

Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution. The resulting datasets are quite large (with scales of TB/hour in some cases), which has presented a barrier to routine open sharing of this data, slowing progress in reproducible research. State of the art methods for analyzing this data are based on non-negative matrix factorization (NMF); these approaches solve a non-convex optimization problem, and are highly effective when good initializations are available, but can break down e.g. in low-SNR settings where common initialization approaches fail.\n\nHere we introduce an improved approach to compressing and denoising functional imaging data. The method is based on a spatially-localized penalized matrix decomposition (PMD) of the data to separate (low-dimensional) signal from (temporally-uncorrelated) noise. This approach can be applied in parallel on local spatial patches and is therefore highly scalable, does not impose non-negativity constraints or require stringent identifiability assumptions (leading to significantly more robust results compared to NMF), and estimates all parameters directly from the data, so no hand-tuning is required. We have applied the method to a wide range of functional imaging data (including one-photon, two-photon, three-photon, widefield, somatic, axonal, dendritic, calcium, and voltage imaging datasets): in all cases, we observe ~2-4x increases in SNR and compression rates of 20-300x with minimal visible loss of signal, with no adjustment of hyperparameters; this in turn facilitates the process of demixing the observed activity into contributions from individual neurons. We focus on two challenging applications: dendritic calcium imaging data and voltage imaging data in the context of optogenetic stimulation. In both cases, we show that our new approach leads to faster and much more robust extraction of activity from the video data.

neuroscience↗

bioRxiv2018

Fusion expression and anti-Aspergillus flavus activity of a novel inhibitory protein DN-AflR

The regulatory gene (aflR) of aflatoxin encodes AflR, a positive regulator that activates transcriptional pathway of genes in aflatoxin biosynthesis. New L-Asp-L-Asn (DN) extracted from Bacillus megaterium inhibited the growth of A. flavus had been elucidated in our laboratory. The genes encoding DN and binuclear zinc finger cluster protein of AflR were fused, then fusion protein could compete with the AflS-AflR complex for the AflR binding site and significantly improve anti-A. flavus activity of DN. The fusion gene dn-aflR was cloned into pET32a and recombinant plasmid was introduced into Escherichia coli BL21. The highest expression was observed after 10 h induction and purified by affinity chromatography column. Compared with DN, the novel fusion protein DN-AflR significantly inhibited the growth of A. flavus and biosynthesis of aflatoxin B1. This study promoted the use of competitive inhibition of fusion proteins to reduce the expression of regulatory genes in the biosynthetic pathway of aflatoxin. Moreover, it provided more supports for deep research and industrialization of such novel, anti-A. flavus bio-inhibitors.\n\nIMPORTANCEAflatoxin contamination has seriously influence on export of agricultural products, income of farmers and economic development. Biological methods, especially using antagonistic microorganisms to inhibit aflatoxin biosynthesis gradually become the hot spot in recent years. DN (L-Asp-L-Asn) from Bacillus megaterium, which could inhibit growth of Aspergillus flavus and synthesis of aflatoxin, has been identified. In this report, we fused the genes encoding inhibitory peptides (DN) and specific zinc finger cluster protein, and expressed the novel anti-A. flavus protein in Escherichia coli. Compared with DN, the inhibitory ability of novel protein has been improved significantly. This research showed fusion expression of anti-fungal proteins, such as DN-AflR, is a promising method to economically improve the inhibitory activity of bio-inhibitors for A. flavus.

microbiology↗

bioRxiv2018

TP53I11 Suppresses Extracellular Matrix-independent Survival and Mesenchymal Transition in Mammary Epithelial Cells

Extracellular matrix (ECM)-independent survival is an essential prerequisite for tumor metastasis and a hallmark of epithelial cancer stem cells and epithelial-mesenchymal transition (EMT). We found that, in MCF10A and MDA-MB-231 cells, loss of TP53I11 (Tumor Protein P53 Inducible Protein 11) enhanced the ECM-independent survival and suppressed glucose starvation induced cell death by increasing the activation of AMPK that confer cells metabolic flexibility to survive under stress conditions. We show here that, TP53I11 enhanced glycolysis and promoted proliferation of MCF10A and MDA-MB-231 cells in normal culture, but exerted negative effect on EMT, cell migration and invasion, and its overexpression suppressed tumor progression and metastasis of MDA-MB-231 cells in vivo. Considering cancer cells also are confronted with the hostile environment such as nutrient scarcity during tumorigenesis and metastasis, our findings suggested that the disruption of metabolic flexibility by TP53I11 through inhibiting AMPK activation resulted in the suppression of tumorigenesis and metastasis of breast cancer.

molecular biology↗

bioRxiv2018

Identification of protein abundance changes in biopsy-level hepatocellular carcinoma tissues using PCT-SWATH

In this study, we optimized the pressure-cycling technology (PCT) and SWATH mass spectrometry workflow to analyze biopsy-level tissue samples (2 mg wet weight) from 19 hepatocellular carcinoma (HCC) patients. Using OpenSWATH and pan-human spectral library, we quantified 11,787 proteotypic peptides from 2,579 SwissProt proteins in 76 HCC tissue samples within about 9 working days (from receiving tissue to SWATH data). The coefficient of variation (CV) of peptide yield using PCT was 32.9%, and the R2 of peptide quantification was 0.9729. We identified protein changes in malignant tissues compared to matched control samples in HCC patients, and further stratified patient samples into groups with high -fetoprotein (AFP) expression or HBV infection. In aggregate, the data identified 23 upregulated pathways and 13 ones. We observed enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues. 16 proteins of high documented relevance to HCC are highlighted in our data. We also identified changes of virus-infection-related proteins including PKM, CTPS1 and ALDOB in the HBV+ HCC subcohort. In conclusion, we demonstrate the practicality of performing proteomic analysis of biopsy-level tissue samples with PCT-SWATH methodology with moderate effort and within a relatively short timeframe.

systems biology↗

bioRxiv2018

Xist Intron 1 Repression by TALE Transcriptional Factor Improves Somatic Cell Reprogamming in Mice

Xist is the master regulator of X chromosome inactivation (XCI). In order to further understand the Xist locus in reprogramming of somatic cells to induced pluripotent stem cells (iPSCs) and in somatic cell nuclear transfer (SCNT), we tested transcription-factor-like effectors (TALE)-based designer transcriptional factors (dTFs), which were specific to numerous regions at the Xist locus. We report that the selected dTF repressor 6 (R6) binding the intron 1 of Xist, which did not affect Xist expression in mouse embryonic fibroblasts (MEFs), substantially improved the iPSC generation and the SCNT preimplantation embryo development. Conversely, the dTF activator targeting the same genomic region of R6 decreased iPSC formation, and blocked SCNT-embryo development. These results thus uncover the critical requirement for the Xist locus in epigenetic resetting, which is not directly related to Xist transcription. This may provide a unique route to improving the reprogramming.

developmental biology↗

bioRxiv2017

Three-photon fluorescence microscopy with an axially elongated Bessel focus

Volumetric imaging tools that are simple to adopt, flexible, and robust, are in high demand in the field of neuroscience, where the ability to image neurons and their networks with high spatiotemporal resolution is essential. Using an axially elongated focus approximating a Bessel beam, in combination with two-photon fluorescence microscopy, has proven successful at such an endeavor. Here we demonstrate three-photon fluorescence imaging with an axially extended Bessel focus. We use an axicon-based module which allowed for the generation of Bessel foci of varying numerical aperture and axial length, and apply this volumetric imaging tool to image mouse brain slices and for in vivo imaging of the mouse brain.

neuroscience↗

bioRxiv2017

Boosting Gene Expression Clustering with System-Wide Biological Information: A Robust Autoencoder Approach

Gene expression analysis provides genome-wide insights into the transcriptional activity of a cell. One of the first computational steps in exploration and analysis of the gene expression data is clustering. With a number of standard clustering methods routinely used, most of the methods do not take prior biological information into account. In this paper, we propose a new approach for gene expression clustering analysis. The approach benefits from a new deep learning architecture, Robust Autoencoder, which provides a more accurate high-level representation of the feature sets, and from incorporating prior biological information into the clustering process. We tested our approach on two distinct gene expression datasets and compared the performance with two widely used clustering methods, hierarchical clustering and k-means, as well as with a recent deep learning clustering approach. As a result, our approach outperformed all other clustering methods on the labeled yeast gene expression dataset. Furthermore we showed that it is better in identifying the functionally common clusters than k-means on the unlabeled human gene expression dataset. The results demonstrate that our new deep learning architecture could generalize well the specific properties of gene expression profiles. Furthermore, the results confirm our hypothesis that the prior biological network knowledge could be helpful in the gene expression clustering task.

bioinformatics↗

bioRxiv2017

Strong positive biodiversity-productivity relationships in a subtropical forest experiment

Forest ecosystems contribute substantially to global terrestrial primary productivity and climate regulation, but, in contrast to grasslands, experimental evidence for a positive biodiversity-productivity relationship in highly diverse forests is still lacking1. Here, we provide such evidence from a large forest biodiversity experiment with a novel design2 in subtropical China. Productivity (stand-level tree basal area, aboveground volume and carbon and their annual increment) increased linearly with the logarithm of tree species richness. Additive partitioning3 showed that increasing positive complementarity effects combined with weakening negative selection effects caused a strengthening of the relationship over time. In 2-species mixed stands, complementary effects increased with functional distance and selection effects with vertical crown dissimilarity between species. Understorey shrubs reduced stand-level tree productivity, but this effect of competition was attenuated by shrub species richness, indicating that a diverse understorey may facilitate overall ecosystem functioning. Identical biodiversity-productivity relationships were found in plots of different size, suggesting that extrapolation to larger scales is possible. Our results highlight the potential of multi-species afforestation strategies to simultaneously contribute to mitigation of climate change and biodiversity restoration.

ecology↗

bioRxiv2017

HPCDb: an integrated database of pancreatic cancer

We have established a database of Human Pancreatic Cancer (HPCDb) through effectively mining, extracting, analyzing, and integrating PC-related genes, single-nucleotide polymorphisms (SNPs), and microRNAs (miRNAs), now available online at http://www.pancancer.org/. Data were extracted from established databases, [≥]5 published literature (PubMed), and microarray chips (screening of differentially expressed genes using limma package in R, |log2 fold change (FC)| > 1). Further, protein-protein interactions (PPIs) were investigated through the Human Protein Reference Database. miRNA-target relationships were also identified using the online software TargetScan. Currently, HPCDb contains 3284 genes, 120 miRNAs, 589 SNPs, 10,139 PPIs, and 3904 miRNA-target pairs. The detailed information on PC-related genes (e.g., gene identifier (ID), symbol, synonyms, full name, chip sets, expression alteration, PubMed ID, and PPIs), miRNAs (e.g., accession number, chromosome location, related disease, PubMed ID, and miRNA-target interactions), and SNPs (e.g., SNP ID, allele, gene, PubMed ID, chromosome location, and disease) is presented through user-friendly query interfaces or convenient links to NCBI GEO, NCBI PubMed, NCBI Gene, NCBI dbSNP, and miRBase. Overall, HPCDb provides biologists with relevant information on human PC-related molecules at multiple levels, helping to generate new hypotheses or identify candidate markers.

bioinformatics↗

bioRxiv2017

A general method to fine-tune fluorophores for live-cell and in vivo imaging

AO_SCPCAPBSTRACTC_SCPCAPPushing the frontier of fluorescence microscopy requires the design of enhanced fluorophores with finely tuned properties. We recently discovered that incorporation of four-membered azetidine rings into classic fluorophore structures elicits substantial increases in brightness and photostability, resulting in the Janelia Fluor (JF) series of dyes. Here, we refine and extend this strategy, showing that incorporation of 3-substituted azetidine groups allows rational tuning of the spectral and chemical properties with unprecedented precision. This strategy yields a palette of new fluorescent and fluorogenic labels with excitation ranging from blue to the far-red with utility in live cells, tissue, and animals.

cell biology↗

bioRxiv2016

lncRNA-screen: an interactive platform for computationally screening long non-coding RNAs in large genomics datasets

Long non-coding RNAs (lncRNAs) have emerged as a class of factors that are important for regulating development and cancer. Computational prediction of lncRNAs from ultra-deep RNA sequencing has been successful in identifying candidate lncRNAs. However, the complexity of handling and integrating different types of genomics data poses significant challenges to experimental laboratories that lack extensive genomics expertise. To address this issue, we have developed lncRNA-screen, a comprehensive pipeline for computationally screening putative lncRNA transcripts over large multimodal datasets. The main objective of this work is to facilitate the computational discovery of lncRNA candidates to be further examined by functional experiments. lncRNA-screen provides a fully automated easy-to-run pipeline which performs data download, RNA-seq alignment, assembly, quality assessment, transcript filtration, novel lncRNA identification, coding potential estimation, expression level quantification, histone mark enrichment profile integration, differential expression analysis, annotation with other type of segmented data (CNVs, SNPs, Hi-C, etc.) and visualization. Importantly, lncRNA-screen generates an interactive report summarizing all interesting lncRNA features including genome browser snapshots and lncRNA-mRNA interactions based on Hi-C data. In summary, our pipeline provides a comprehensive solution for lncRNA discovery and an intuitive interactive report for identifying promising lncRNA candidates. lncRNA-screen is available as free open-source software on GitHub.

bioinformatics↗